Data Scientist III – OHS TTA Hub

Missing Link Security

Northern (KY)

Remote

USD 110,000 - 160,000

Full time

2 days ago
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Job summary

Missing Link Security seeks a Data Scientist III to support OHS TTA Hub on the HHS/ACF program. Remote work with core hours 10:00–16:00 ET; requires US citizenship and ability to obtain Public Trust clearance and PIV card.

Responsibilities include leading statistical, ML, and AI model development for TTA reporting, ensuring explainability, documenting use cases, and validating models with rigorous experimentation and monitoring. Contingent upon contract award.

Qualifications

  • 7+ years of experience in applied statistics or data science
  • Experience with production ML or advanced analytics and model validation
  • Bachelor's degree or equivalent in a quantitative field
  • Ability to obtain a Public Trust clearance
  • Experience with model validation and experimental design

Responsibilities

  • Lead development of statistical, ML, and AI models for TTA reporting
  • Document AI use cases and ensure explainability
  • Define outcomes, baselines, and validation methods
  • Monitor model performance and address data leakage/bias
  • Collaborate with data, engineering, security, and program teams
  • Communicate analytical findings clearly to stakeholders
  • Prototype and productionize validated analytics approaches
  • Promote reproducibility throughout the analytics lifecycle

Skills

Statistical modeling
Experiment design
Model validation
Communication of findings
Analytical thinking
Problem solving

Education

Bachelor's degree in statistics, data science, computer science, or related quantitative field
Advanced degree in statistics, data science, or related field

Tools

Python
R
Cloud data warehouses
Distributed data systems

Job description

All Jobs > Data Scientist III – OHS TTA Hub

Location: Remote
Schedule: Full-Time; must be available during core hours of 10:00 a.m.–4:00 p.m. Eastern
Citizenship: U.S. citizenship required
Clearance: Must be able to obtain and maintain a Public Trust clearance and obtain a PIV card
Travel: Occasional travel may be required
Position Status: Contingent upon contract award

Missing Link Security is seeking an experienced Data Scientist III to support the Office of Head Start (OHS) Training and Technical Assistance Data Platform, known as the TTA Hub, in support of the U.S. Department of Health and Human Services (HHS), Administration for Children and Families (ACF).

The Data Scientist III will develop and validate advanced analytics and, when prioritized, artificial intelligence capabilities that help OHS better understand training and technical assistance needs and outcomes. This role will apply rigorous statistical and data science methods while ensuring that models and analytical approaches are explainable, validated, reproducible, and appropriately monitored.

This is a Key Personnel position and will be named in our proposal.

Responsibilities
  • Lead development of statistical, machine learning, and, when prioritized, AI models supporting TTA reporting, trend analysis, and actionable insights.
  • Ensure each AI use case is appropriately documented and explainable.
  • Define expected outcomes, baselines, experimental designs, and validation approaches before deployment.
  • Establish methods for evaluating uncertainty and monitoring model performance.
  • Develop and maintain appropriate model documentation.
  • Partner with the Senior Data Analyst on data definitions, data quality, and responsible interpretation of analytical results.
  • Communicate analytical findings and their implications clearly to program leaders.
  • Prototype and productionize approved analytical and modeling approaches in collaboration with engineering and security team members.
  • Develop and apply tests addressing data leakage, bias, privacy, and performance.
  • Promote reproducibility and appropriate validation throughout the analytics and modeling lifecycle.
Requirements
  • Seven (7) or more years of experience in applied statistics or data science, including experience with production machine learning or advanced analytics and model validation.
  • Bachelor's degree in statistics, data science, computer science, or a related quantitative field, or equivalent demonstrated experience.
  • Strong experience with statistical modeling and regression.
  • Experience designing and evaluating experiments.
  • Experience with optimization methods.
  • Proficiency with Python or R.
  • Experience working with cloud data warehouses.
  • Experience working with distributed data.
  • Demonstrated experience with analytical and model validation.
  • Ability to obtain and maintain a Public Trust clearance and obtain a Personal Identity Verification (PIV) card.
Preferred Qualifications
  • Advanced degree in statistics, data science, computer science, or another related quantitative field.
  • Experience with responsible AI governance.
  • Experience applying Natural Language Processing (NLP) to narrative reports.
  • Experience with operational machine learning monitoring.
Ideal Candidate

The ideal candidate combines strong statistical and data science expertise with a disciplined approach to validation, interpretation, and responsible use of advanced analytics. This individual understands that a successful model must not only perform well but also be explainable, reproducible, appropriately monitored, and suitable for the context in which it will be used.

We are looking for someone who can move comfortably between research, analysis, experimentation, and production implementation while collaborating effectively with data, engineering, security, and program stakeholders. The successful candidate will be analytical, thoughtful, curious, and able to communicate sophisticated findings clearly to both technical and non-technical audiences.

Missing Link Security is an Equal Opportunity Employer. We consider all qualified applicants for employment without regard to race, color, religion, sex, national origin, age, disability, veteran status, or any other characteristic protected by applicable federal, state, or local law.

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